import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin





class UpperCAmelCase		(   __A   ,			__A   ,			__A    ):


				'''simple docstring'''






				@register_to_config
				def __init__(		self						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase = False						,      ):



						"""simple docstring"""





						super().__init__()

						A_						:							Optional[int]      = nn.Embedding(lowercase						,      lowercase   )

						A_						:							Any      = nn.Embedding(lowercase						,      lowercase   )
						A_						:							int      = False

						A_						:							Tuple      = nn.Dropout(p=lowercase   )

						A_						:							List[Any]      = TaConfig(
						    vocab_size=lowercase						,      d_model=lowercase						,      num_heads=lowercase						,      d_kv=lowercase						,      d_ff=lowercase						,      dropout_rate=lowercase						,      feed_forward_proj=lowercase						,      is_decoder=lowercase						,      is_encoder_decoder=lowercase						,      )

						A_						:							List[str]      = nn.ModuleList()
						for lyr_num in range(lowercase   ):
								A_						:							Dict      = TaBlock(lowercase   )
								self.encoders.append(lowercase   )

						A_						:							Any      = TaLayerNorm(lowercase   )
						A_						:							Optional[int]      = nn.Dropout(p=lowercase   )







				def     lowerCAmelCase_  (		self						,      lowercase						,      lowercase   ):



						"""simple docstring"""





						A_						:							Any      = self.token_embedder(lowercase   )

						A_						:							List[Any]      = encoder_input_tokens.shape[1]
						A_						:							int      = torch.arange(lowercase						,      device=encoder_input_tokens.device   )
						x += self.position_encoding(lowercase   )

						A_						:							Dict      = self.dropout_pre(lowercase   )

						# inverted the attention mask
						A_						:							List[Any]      = encoder_input_tokens.size()
						A_						:							Dict      = self.get_extended_attention_mask(lowercase						,      lowercase   )

						for lyr in self.encoders:
								A_						:							List[str]      = lyr(lowercase						,      lowercase   )[0]
						A_						:							Optional[int]      = self.layer_norm(lowercase   )

						return self.dropout_post(lowercase   ), encoder_inputs_mask







import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


_UpperCAmelCase          =						pytest.mark.integration




@pytest.mark.parametrize('path'		,['paws', 'csv']      )
def 							UpperCamelCase		(			__lowercase		:					Optional[Any]		,__lowercase		:					Tuple      ):
		'''simple docstring'''




		inspect_dataset(__lowercase		,__lowercase      )
		A_						:							Optional[Any]      = path + '.py'
		assert script_name in os.listdir(__lowercase      )
		assert "__pycache__" not in os.listdir(__lowercase      )




@pytest.mark.filterwarnings('ignore:inspect_metric is deprecated:FutureWarning'      )
@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'      )
@pytest.mark.parametrize('path'		,['accuracy']      )
def 							UpperCamelCase		(			__lowercase		:					Any		,__lowercase		:					Union[str, Any]      ):
		'''simple docstring'''




		inspect_metric(__lowercase		,__lowercase      )
		A_						:							Optional[Any]      = path + '.py'
		assert script_name in os.listdir(__lowercase      )
		assert "__pycache__" not in os.listdir(__lowercase      )




@pytest.mark.parametrize(
    'path, config_name, expected_splits'		,[
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					List[str]		,__lowercase		:					Dict		,__lowercase		:					Dict      ):
		'''simple docstring'''




		A_						:							List[Any]      = get_dataset_config_info(__lowercase		,config_name=__lowercase      )
		assert info.config_name == config_name
		assert list(info.splits.keys()      ) == expected_splits




@pytest.mark.parametrize(
    'path, config_name, expected_exception'		,[
        ('paws', None, ValueError),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Dict		,__lowercase		:					List[Any]		,__lowercase		:					int      ):
		'''simple docstring'''




		with pytest.raises(__lowercase      ):
				get_dataset_config_info(__lowercase		,config_name=__lowercase      )




@pytest.mark.parametrize(
    'path, expected'		,[
        ('squad', 'plain_text'),
        ('acronym_identification', 'default'),
        ('lhoestq/squad', 'plain_text'),
        ('lhoestq/test', 'default'),
        ('lhoestq/demo1', 'lhoestq--demo1'),
        ('dalle-mini/wit', 'dalle-mini--wit'),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					str		,__lowercase		:					str      ):
		'''simple docstring'''




		A_						:							Any      = get_dataset_config_names(__lowercase      )
		assert expected in config_names




@pytest.mark.parametrize(
    'path, expected_configs, expected_splits_in_first_config'		,[
        ('squad', ['plain_text'], ['train', 'validation']),
        ('dalle-mini/wit', ['dalle-mini--wit'], ['train']),
        ('paws', ['labeled_final', 'labeled_swap', 'unlabeled_final'], ['train', 'test', 'validation']),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Tuple		,__lowercase		:					str		,__lowercase		:					Optional[Any]      ):
		'''simple docstring'''




		A_						:							Optional[int]      = get_dataset_infos(__lowercase      )
		assert list(infos.keys()      ) == expected_configs
		A_						:							Any      = expected_configs[0]
		assert expected_config in infos
		A_						:							Tuple      = infos[expected_config]
		assert info.config_name == expected_config
		assert list(info.splits.keys()      ) == expected_splits_in_first_config




@pytest.mark.parametrize(
    'path, expected_config, expected_splits'		,[
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Any		,__lowercase		:					Optional[Any]		,__lowercase		:					Dict      ):
		'''simple docstring'''




		A_						:							Optional[Any]      = get_dataset_infos(__lowercase      )
		assert expected_config in infos
		A_						:							str      = infos[expected_config]
		assert info.config_name == expected_config
		assert list(info.splits.keys()      ) == expected_splits




@pytest.mark.parametrize(
    'path, config_name, expected_exception'		,[
        ('paws', None, ValueError),
    ]		,)
def 							UpperCamelCase		(			__lowercase		:					Tuple		,__lowercase		:					Tuple		,__lowercase		:					str      ):
		'''simple docstring'''




		with pytest.raises(__lowercase      ):
				get_dataset_split_names(__lowercase		,config_name=__lowercase      )






